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Full Scoreboard »» |
Chicago Wolves Team Overall:67 1-1-0, 2pts · 3rd in Conférence EST |
Player | # | POS | CON | Age | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | Overall | Condition | Contract | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | LW/RW | 100.00 | 28 | 71 | 34 | 92 | 66 | 73 | 85 | 87 | 65 | 61 | 64 | 69 | 84 | 65 | 71 | 69 | 0 | 40 | 73 | 100.00 | 2,100,000$/1yrs | ||
![]() | 0 | C/RW | 100.00 | 25 | 72 | 37 | 86 | 71 | 69 | 84 | 79 | 68 | 82 | 67 | 65 | 83 | 64 | 67 | 69 | 0 | 40 | 73 | 100.00 | 1,350,000$/1yrs | ||
![]() | 0 | C/LW | 100.00 | 25 | 85 | 48 | 83 | 68 | 81 | 82 | 85 | 69 | 74 | 62 | 70 | 73 | 69 | 65 | 67 | 0 | 40 | 73 | 100.00 | 725,000$/3yrs | ||
![]() | 0 | C | 100.00 | 34 | 73 | 34 | 92 | 65 | 70 | 79 | 82 | 67 | 69 | 66 | 67 | 65 | 68 | 81 | 74 | 0 | 40 | 72 | 100.00 | 4,125,000$/1yrs | ||
![]() | 0 | C | 100.00 | 26 | 83 | 78 | 84 | 63 | 97 | 76 | 78 | 60 | 85 | 64 | 61 | 71 | 58 | 67 | 69 | 0 | 40 | 71 | 100.00 | 675,000$/1yrs | ||
![]() | 0 | RW | 100.00 | 24 | 80 | 38 | 91 | 67 | 92 | 76 | 81 | 66 | 54 | 65 | 63 | 59 | 65 | 64 | 66 | 0 | 40 | 71 | 100.00 | 1,633,333$/1yrs | ||
![]() | 0 | RW | 100.00 | 24 | 90 | 81 | 70 | 66 | 85 | 79 | 86 | 64 | 73 | 67 | 63 | 62 | 58 | 65 | 67 | 0 | 40 | 71 | 100.00 | 725,000$/3yrs | ||
![]() | 0 | C/RW | 100.00 | 23 | 76 | 43 | 91 | 73 | 83 | 59 | 70 | 66 | 33 | 77 | 70 | 62 | 25 | 46 | 46 | 0 | 40 | 71 | 100.00 | 1,075,833$/1yrs | ||
![]() | 0 | C/RW | 100.00 | 22 | 73 | 38 | 87 | 65 | 80 | 79 | 85 | 67 | 76 | 66 | 65 | 64 | 68 | 63 | 66 | 0 | 40 | 71 | 100.00 | 1,081,667$/1yrs | ||
![]() | 0 | C/LW/RW | 100.00 | 29 | 76 | 38 | 84 | 63 | 74 | 79 | 86 | 62 | 73 | 66 | 61 | 70 | 63 | 73 | 71 | 0 | 40 | 70 | 100.00 | 2,000,000$/1yrs | ||
![]() | 0 | LW | 100.00 | 26 | 86 | 82 | 59 | 65 | 80 | 76 | 85 | 64 | 56 | 63 | 62 | 56 | 61 | 67 | 68 | 0 | 40 | 69 | 100.00 | 925,000$/1yrs | ||
![]() | 0 | C/RW | 100.00 | 26 | 57 | 35 | 94 | 63 | 66 | 89 | 86 | 64 | 74 | 65 | 66 | 62 | 64 | 67 | 69 | 0 | 40 | 69 | 100.00 | 750,000$/1yrs | ||
![]() | 0 | D | 100.00 | 23 | 64 | 34 | 75 | 71 | 73 | 87 | 90 | 66 | 30 | 72 | 61 | 70 | 52 | 64 | 66 | 0 | 40 | 71 | 100.00 | 925,000$/1yrs | ||
![]() | 0 | D | 100.00 | 28 | 66 | 36 | 89 | 65 | 78 | 86 | 81 | 62 | 30 | 71 | 59 | 63 | 52 | 69 | 71 | 0 | 40 | 70 | 100.00 | 725,000$/1yrs | ||
![]() | 0 | D | 100.00 | 27 | 85 | 73 | 91 | 60 | 95 | 79 | 74 | 55 | 30 | 67 | 58 | 63 | 51 | 67 | 69 | 0 | 40 | 69 | 100.00 | 850,000$/1yrs | ||
![]() | 0 | D | 100.00 | 23 | 64 | 35 | 86 | 65 | 77 | 87 | 81 | 63 | 30 | 73 | 55 | 73 | 49 | 63 | 64 | 0 | 40 | 69 | 100.00 | 925,000$/1yrs | ||
![]() | 0 | D | 100.00 | 29 | 86 | 38 | 91 | 60 | 75 | 83 | 85 | 62 | 30 | 61 | 57 | 68 | 52 | 70 | 72 | 0 | 40 | 69 | 100.00 | 675,000$/1yrs | ||
![]() | 0 | D | 100.00 | 21 | 77 | 42 | 78 | 63 | 88 | 84 | 78 | 62 | 30 | 61 | 59 | 64 | 53 | 62 | 64 | 0 | 40 | 68 | 100.00 | 894,167$/2yrs | ||
Scratches | ||||||||||||||||||||||||||
![]() | 0 | LW | 100.00 | 23 | 79 | 81 | 77 | 58 | 96 | 76 | 85 | 61 | 54 | 59 | 60 | 55 | 61 | 64 | 66 | 0 | 40 | 68 | 100.00 | 995,833$/3yrs | ||
![]() | 0 | RW | 100.00 | 22 | 62 | 38 | 80 | 64 | 63 | 86 | 82 | 63 | 64 | 61 | 62 | 60 | 63 | 64 | 65 | 0 | 40 | 67 | 100.00 | 925,000$/1yrs | ||
![]() | 0 | LW | 100.00 | 21 | 68 | 38 | 82 | 62 | 79 | 78 | 71 | 60 | 59 | 57 | 58 | 61 | 59 | 62 | 64 | 0 | 40 | 66 | 100.00 | 1,208,333$/2yrs | ||
![]() | 0 | C/RW | 100.00 | 21 | 62 | 37 | 90 | 58 | 69 | 82 | 76 | 57 | 66 | 56 | 59 | 55 | 58 | 62 | 63 | 0 | 40 | 65 | 100.00 | 910,833$/2yrs | ||
![]() | 0 | C | 100.00 | 23 | 67 | 36 | 93 | 58 | 76 | 67 | 71 | 53 | 58 | 54 | 55 | 57 | 53 | 64 | 66 | 0 | 40 | 64 | 100.00 | 1,106,666$/1yrs | ||
![]() | 0 | LW | 100.00 | 21 | 72 | 39 | 74 | 53 | 81 | 67 | 72 | 54 | 51 | 55 | 56 | 57 | 53 | 62 | 64 | 0 | 40 | 64 | 100.00 | 905,000$/3yrs | ||
![]() | 0 | C | 100.00 | 20 | 58 | 39 | 82 | 57 | 67 | 75 | 80 | 56 | 63 | 55 | 58 | 53 | 54 | 61 | 63 | 0 | 40 | 64 | 100.00 | 875,000$/3yrs | ||
![]() | 0 | C | 100.00 | 22 | 63 | 37 | 71 | 58 | 69 | 73 | 74 | 57 | 63 | 56 | 55 | 54 | 58 | 62 | 64 | 0 | 40 | 63 | 100.00 | 883,333$/2yrs | ||
![]() | 0 | C | 100.00 | 19 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 40 | 17 | 100.00 | 925,000$/2yrs | ||
![]() | 0 | D | 100.00 | 26 | 81 | 41 | 82 | 59 | 89 | 77 | 78 | 56 | 30 | 58 | 57 | 64 | 49 | 67 | 69 | 0 | 40 | 67 | 100.00 | 700,000$/1yrs | ||
![]() | 0 | D | 100.00 | 23 | 58 | 39 | 77 | 57 | 69 | 66 | 72 | 56 | 30 | 57 | 52 | 53 | 45 | 64 | 66 | 0 | 40 | 63 | 100.00 | 925,000$/1yrs | ||
TEAM AVERAGE | 100.00 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
Goalie | # | CON | AGE | Age | CK | FG | DI | SK | ST | EN | DU | PH | FO | PA | SC | DF | PS | EX | LD | PO | MO | Overall | CONTRACT |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
![]() | 0 | 100.00 | 24 | 83 | 79 | 82 | 83 | 83 | 82 | 64 | 73 | 0 | 40 | 71 | 910,833$/1yrs | ||||||||
![]() | 0 | 100.00 | 21 | 75 | 77 | 78 | 75 | 75 | 74 | 62 | 67 | 0 | 40 | 66 | 910,833$/2yrs | ||||||||
Scratches | |||||||||||||||||||||||
![]() | 0 | 100.00 | 21 | 73 | 80 | 81 | 73 | 73 | 72 | 62 | 67 | 0 | 40 | 65 | 925,000$/3yrs | ||||||||
![]() | 0 | 100.00 | 23 | 66 | 67 | 68 | 66 | 66 | 65 | 63 | 69 | 0 | 40 | 61 | 925,000$/1yrs | ||||||||
TEAM AVERAGE | 100.00 |
Coaches Name | PH | DF | OF | PD | EX | LD | PO | CNT | Age | Contract | Salary |
---|---|---|---|---|---|---|---|---|---|---|---|
Rod Brind'Amour | 82 | 95 | 89 | 83 | 77 | 72 | 73 | CAN | 52 | 1 | 575,000$ |
General Manager |
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Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | Player Name | Team Name | # | POS | GP | G | A | P | +/- | PIM | PIM5 | HIT | SHT | OSB | OSM | SHT% | SB | MP | AMG | PPG | PPA | PPP | PPM | PKG | PKA | PKP | PKM | GW | GT | FO% | FOT | GA | TA | EG | HT | P/20 | PSG | PSS |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Sean Durzi | D | 2 | 0 | 3 | 3 | 2 | 0 | 0 | 5 | 1 | 0 | 3 | 0.00% | 1 | 26.52 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 2 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 1.13 | 0 | 0 | |||
2 | Gustav Lindstrom | D | 2 | 2 | 0 | 2 | -1 | 0 | 0 | 0 | 5 | 1 | 5 | 40.00% | 2 | 22.95 | 2 | 0 | 2 | 8 | 0 | 0 | 0 | 4 | 1 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.87 | 0 | 0 | |||
3 | Jordan Martinook | C/LW/RW | 2 | 1 | 1 | 2 | 1 | 0 | 0 | 0 | 4 | 2 | 0 | 25.00% | 0 | 16.24 | 0 | 1 | 1 | 7 | 0 | 0 | 0 | 0 | 0 | 0 | 100.00% | 1 | 0 | 0 | 0 | 0 | 1.23 | 0 | 0 | |||
4 | Keegan Kolesar | RW | 2 | 2 | 0 | 2 | 0 | 0 | 0 | 1 | 4 | 1 | 1 | 50.00% | 0 | 11.18 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 1.79 | 0 | 0 | |||
5 | Brendan Lemieux | LW | 2 | 0 | 1 | 1 | 0 | 0 | 0 | 3 | 2 | 0 | 1 | 0.00% | 0 | 11.55 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 2 | 0 | 0 | 0 | 0 | 0.87 | 0 | 0 | |||
6 | Dean Kukan | D | 2 | 0 | 1 | 1 | 2 | 0 | 0 | 6 | 3 | 1 | 1 | 0.00% | 1 | 26.40 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 2 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.38 | 0 | 0 | |||
7 | Mathieu Perreault | C | 2 | 0 | 1 | 1 | -1 | 0 | 0 | 1 | 3 | 5 | 4 | 0.00% | 0 | 18.80 | 0 | 1 | 1 | 7 | 0 | 0 | 0 | 2 | 0 | 0 | 57.14% | 49 | 0 | 0 | 0 | 0 | 0.53 | 0 | 0 | |||
8 | Nicholas Merkley | C/RW | 2 | 1 | 0 | 1 | -1 | 0 | 0 | 3 | 9 | 2 | 4 | 11.11% | 0 | 18.62 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 1 | 0 | 0 | 0.00% | 2 | 0 | 0 | 0 | 0 | 0.54 | 0 | 0 | |||
9 | Yakov Trenin | C/LW | 2 | 0 | 1 | 1 | -1 | 5 | 5 | 11 | 10 | 3 | 6 | 0.00% | 0 | 19.10 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 1 | 0 | 0 | 33.33% | 3 | 0 | 0 | 0 | 0 | 0.52 | 0 | 0 | |||
10 | Brock McGinn | LW/RW | 2 | 0 | 0 | 0 | -1 | 0 | 0 | 0 | 3 | 1 | 7 | 0.00% | 0 | 22.65 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 4 | 0 | 0 | 0.00% | 3 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |||
11 | Carl Dahlstrom | D | 2 | 0 | 0 | 0 | -1 | 0 | 0 | 6 | 2 | 1 | 0 | 0.00% | 0 | 22.72 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 3 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |||
12 | Dylan Sikura | C/RW | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0.00% | 1 | 11.30 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 44.00% | 25 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |||
13 | Frederik Gauthier | C | 2 | 0 | 0 | 0 | 1 | 2 | 0 | 3 | 5 | 2 | 5 | 0.00% | 0 | 12.26 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 62.50% | 24 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |||
14 | Jake Evans | C/RW | 2 | 0 | 0 | 0 | -1 | 0 | 0 | 5 | 3 | 1 | 3 | 0.00% | 0 | 18.23 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 0 | 50.00% | 10 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |||
15 | Julien Gauthier | RW | 2 | 0 | 0 | 0 | 1 | 2 | 0 | 2 | 1 | 1 | 3 | 0.00% | 0 | 12.59 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 25.00% | 4 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |||
16 | Radim Simek | D | 2 | 0 | 0 | 0 | -2 | 0 | 0 | 6 | 1 | 0 | 0 | 0.00% | 0 | 16.37 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |||
17 | Rasmus Kupari | C/RW | 2 | 0 | 0 | 0 | -1 | 0 | 0 | 6 | 4 | 1 | 2 | 0.00% | 0 | 20.66 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 0 | 0 | 0 | 40.38% | 52 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |||
18 | Alec Regula | D | 2 | 0 | 0 | 0 | -2 | 4 | 0 | 3 | 0 | 1 | 2 | 0.00% | 0 | 16.24 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00% | 0 | 0 | 0 | 0 | 0 | 0.00 | 0 | 0 | |||
Team Total or Average | 36 | 6 | 8 | 14 | -5 | 13 | 5 | 61 | 61 | 24 | 47 | 9.84% | 5 | 18.02 | 2 | 2 | 4 | 80 | 0 | 0 | 0 | 28 | 1 | 0 | 47.43% | 175 | 0 | 0 | 0 | 0 | 0.43 | 0 | 0 |
Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | Goalie Name | Team Name | GP | W | L | OTL | PCT | GAA | MP | PIM | SO | GA | SA | SAR | A | EG | PS % | PSA | ST | BG | S1 | S2 | S3 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Dan Vladar | 2 | 1 | 1 | 0 | 0.893 | 2.77 | 130 | 0 | 0 | 6 | 56 | 0 | 0 | 0 | 0.000 | 0 | 2 | 0 | 0 | 0 | 0 | |
Team Total or Average | 2 | 1 | 1 | 0 | 0.893 | 2.77 | 130 | 0 | 0 | 6 | 56 | 0 | 0 | 0 | 0.000 | 0 | 2 | 0 | 0 | 0 | 0 |
Projected Total Cap Hit | 0$ |
Projected Cap Space | 0$ |
Retains And Buyout Cap Hit | 0$ |
Salary Cap To Date | 0$ |
Players In Salary Cap | 0 |
LTIR Players | 0 |
Player Name | POS | Age | Cap Hit | 2017-18 | 2018-19 | 2019-20 | 2020-21 | 2021-22 | 2022-23 | 2023-24 | 2024-25 |
---|---|---|---|---|---|---|---|---|---|---|---|
Akil Thomas | C/RW | 21 | 910,833$ | 910,833$ | 910,833$ | ||||||
Alec Regula | D | 21 | 894,167$ | 894,167$ | 894,167$ | ||||||
Brendan Lemieux | LW | 26 | 925,000$ | 925,000$ | |||||||
Brock McGinn | LW/RW | 28 | 2,100,000$ | 2,100,000$ | |||||||
Carl Dahlstrom | D | 27 | 850,000$ | 850,000$ | |||||||
Carson Focht | C | 22 | 883,333$ | 883,333$ | 883,333$ | ||||||
Chad Krys | D | 23 | 925,000$ | 925,000$ | |||||||
| 0$ | 0$ | |||||||||
Dean Kukan | D | 28 | 725,000$ | 725,000$ | |||||||
Dillon Hamaliuk | LW | 21 | 905,000$ | 905,000$ | 905,000$ | 905,000$ | |||||
Dillon Heatherington | D | 26 | 700,000$ | 700,000$ | |||||||
Dylan Sikura | C/RW | 26 | 750,000$ | 750,000$ | |||||||
Frederik Gauthier | C | 26 | 675,000$ | 675,000$ | |||||||
German Rubtsov | C | 23 | 1,106,666$ | 1,106,666$ | |||||||
Gustav Lindstrom | D | 23 | 925,000$ | 925,000$ | |||||||
Jake Evans | C/RW | 25 | 1,350,000$ | 1,350,000$ | |||||||
Jordan Martinook | C/LW/RW | 29 | 2,000,000$ | 2,000,000$ | |||||||
Julien Gauthier | RW | 24 | 1,633,333$ | 1,633,333$ | |||||||
Keean Washkurak | C | 20 | 875,000$ | 875,000$ | 875,000$ | 875,000$ | |||||
Keegan Kolesar | RW | 24 | 725,000$ | 725,000$ | 725,000$ | 725,000$ | |||||
| 0$ | 0$ | |||||||||
| 0$ | 0$ | |||||||||
Mathieu Perreault | C | 34 | 4,125,000$ | 4,125,000$ | |||||||
Nicholas Merkley | C/RW | 23 | 1,075,833$ | 1,075,833$ | |||||||
| 0$ | 0$ | |||||||||
Radim Simek | D | 29 | 675,000$ | 675,000$ | |||||||
Rasmus Kupari | C/RW | 22 | 1,081,667$ | 1,081,667$ | |||||||
Riley Tufte | LW | 23 | 995,833$ | 995,833$ | 995,833$ | 995,833$ | |||||
Sampo Ranta | LW | 21 | 1,208,333$ | 1,208,333$ | 1,208,333$ | ||||||
Sean Durzi | D | 23 | 925,000$ | 925,000$ | |||||||
Trey Fix-Wolansky | RW | 22 | 925,000$ | 925,000$ | |||||||
Tyson Foerster | C | 19 | 925,000$ | 925,000$ | 925,000$ | ||||||
Yakov Trenin | C/LW | 25 | 725,000$ | 725,000$ | 725,000$ | 725,000$ |
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Priority | Type | Description |
---|---|---|
1 | | or OR | Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar |
2 | && or AND | Logical "and". Filter the column for content that matches text from either side of the operator. |
3 | /\d/ | Add any regex to the query to use in the query ("mig" flags can be included /\w/mig ) |
4 | < <= >= > | Find alphabetical or numerical values less than or greater than or equal to the filtered query |
5 | ! or != | Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (= ), single (' ) or double quote (" ) to exactly not match a filter. |
6 | " or = | To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query |
7 | - or to | Find a range of values. Make sure there is a space before and after the dash (or the word "to") |
8 | ? | Wildcard for a single, non-space character. |
8 | * | Wildcard for zero or more non-space characters. |
9 | ~ | Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query |
10 | text | Any text entered in the filter will match text found within the column |
# | VS Team | GP | W | L | T | OTW | OTL | SOW | SOL | GF | GA | Diff | P | PCT | G | A | TP | SO | EG | GP1 | GP2 | GP3 | GP4 | SHF | SH1 | SP2 | SP3 | SP4 | SHA | SHB | Pim | Hit | PPA | PPG | PP% | PKA | PK GA | PK% | PK GF | W OF FO | T OF FO | OF FO% | W DF FO | T DF FO | DF FO% | W NT FO | T NT FO | NT FO% | PZ DF | PZ OF | PZ NT | PC DF | PC OF | PC NT | GF% | SH% | SV% | PDO | PDOBRK |
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1 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 6 | 6 | 0 | 2 | 0.500 | 6 | 8 | 14 | 0 | 0 | 3 | 1 | 1 | 1 | 61 | 19 | 14 | 23 | 5 | 56 | 5 | 13 | 61 | 9 | 2 | 22.22% | 4 | 1 | 75.00% | 0 | 35 | 70 | 50.00% | 32 | 67 | 47.76% | 16 | 38 | 42.11% | 51 | 34 | 49 | 15 | 30 | 15 | 44.4% | 9.8% | 89.3% | 99.1 | FUN | |
_Vs Conference | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 6 | 6 | 0 | 2 | 0.500 | 6 | 8 | 14 | 0 | 0 | 3 | 1 | 1 | 1 | 61 | 19 | 14 | 23 | 5 | 56 | 5 | 13 | 61 | 9 | 2 | 22.22% | 4 | 1 | 75.00% | 0 | 35 | 70 | 50.00% | 32 | 67 | 47.76% | 16 | 38 | 42.11% | 51 | 34 | 49 | 15 | 30 | 15 | 44.4% | 9.8% | 89.3% | 99.1 | FUN | |
_Since Last GM Reset | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 6 | 6 | 0 | 2 | 0.500 | 6 | 8 | 14 | 0 | 0 | 3 | 1 | 1 | 1 | 61 | 19 | 14 | 23 | 5 | 56 | 5 | 13 | 61 | 9 | 2 | 22.22% | 4 | 1 | 75.00% | 0 | 35 | 70 | 50.00% | 32 | 67 | 47.76% | 16 | 38 | 42.11% | 51 | 34 | 49 | 15 | 30 | 15 | 44.4% | 9.8% | 89.3% | 99.1 | FUN | |
Total | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 6 | 6 | 0 | 2 | 0.500 | 6 | 8 | 14 | 0 | 0 | 3 | 1 | 1 | 1 | 61 | 19 | 14 | 23 | 5 | 56 | 5 | 13 | 61 | 9 | 2 | 22.22% | 4 | 1 | 75.00% | 0 | 35 | 70 | 50.00% | 32 | 67 | 47.76% | 16 | 38 | 42.11% | 51 | 34 | 49 | 15 | 30 | 15 | 44.4% | 9.8% | 89.3% | 99.1 | FUN |
Puck Time | |
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Offensive Zone | 25 |
Neutral Zone | 15 |
Defensive Zone | 24 |
Puck Time | |
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Offensive Zone Start | 70 |
Neutral Zone Start | 38 |
Defensive Zone Start | 67 |
Puck Time | |
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With Puck | 32 |
Without Puck | 32 |
Faceoffs | |
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Faceoffs Won | 83 |
Faceoffs Lost | 92 |
Team Average Shots after | League Average Shots after | |
---|---|---|
1st Period | 9.5 | 9.57 |
2nd Period | 16.5 | 20.31 |
3rd Period | 28.0 | 30.68 |
Overtime | 30.5 | 31.4 |
Goals in | Team Average Goals after | League Average Goals after |
---|---|---|
1st Period | 1.5 | 0.64 |
2nd Period | 2.0 | 1.65 |
3rd Period | 2.5 | 2.67 |
Overtime | 3.0 | 2.83 |
Even Strenght Goal | 4 |
---|---|
PP Goal | 2 |
PK Goal | 0 |
Empty Net Goal | 0 |
Home | Away | |
---|---|---|
Win | 1 | 0 |
Lost | 1 | 0 |
Overtime Lost | 0 | 0 |
PP Attempt | 9 |
---|---|
PP Goal | 2 |
PK Attempt | 4 |
PK Goal Against | 1 |
Home | |
---|---|
Shots For | 30.5 |
Shots Against | 28.0 |
Goals For | 3.0 |
Goals Against | 3.0 |
Hits | 30.5 |
Shots Blocked | 2.5 |
Pim | 6.5 |
Date | Matchup | Result | Detail | ||
---|---|---|---|---|---|
2023-03-21 | @ | Canucks2,Wolves3 (OT) | RECAP | ||
2023-03-23 | @ | Canucks4,Wolves3 | RECAP | ||
2023-03-25 | @ | ||||
2023-03-27 | @ | ||||
2023-03-29 | @ | ||||
2023-03-31 | @ | ||||
2023-04-02 | @ |
Salary Cap | |||
---|---|---|---|
Players Total Salaries | Retained Salary | Total Cap Hit | Estimated Cap Space |
32,534,992$ | 0$ | 0$ | 75,000,000$ |
Arena | About us | |
---|---|---|
![]() | Name | |
City | Chicago | |
Capacity | 3000 | |
Season Ticket Holders | 0% |
Arena Capacity - Ticket Price Attendance - % | |||||
---|---|---|---|---|---|
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Arena Capacity | 2000 | 1000 | |||
Ticket Price | 35$ | 15$ | $ | $ | $ |
Attendance | 0 | 0 | |||
Attendance PCT | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
Income | |||||
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Home Games Left | Average Attendance - % | Average Income per Game | Year to Date Revenue | Arena Capacity | Team Popularity |
-2 | 0 - 0.00% | 0$ | 0$ | 3000 | 100 |
Expenses | |||
---|---|---|---|
Players Total Salaries | Players Total Average Salaries | Coaches Salaries | Special Salary Cap Value |
32,534,992$ | 32,534,992$ | 0$ | 0$ |
Year To Date Expenses | Salary Cap Per Days | Salary Cap To Date | Luxury Taxe Total |
---|---|---|---|
0$ | 0$ | 0$ | 0$ |
Estimate | |||
---|---|---|---|
Estimated Season Revenue | Remaining Season Days | Expenses Per Days | Estimated Season Expenses |
0$ | 10 | 0$ | 0$ |
Team Total Estimate | |||
---|---|---|---|
Estimated Season Expenses | Estimated Season Salary Cap | Current Bank Account | Projected Bank Account |
0$ | 0$ | 0$ | 0$ |
Sponsors | |||
---|---|---|---|
TV Rights | Primary Sponsor | Secondary Sponsor | Secondary Sponsor |
Left Wing | Center | Right Wing |
---|---|---|
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Defense #1 | Defense #2 | Goalie |
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